Impairment memory monitoring in patients with Wilson's disease
10.3760/cma.j.issn.1674-6554.2014.05.011
- VernacularTitle:肝豆状核变性患者的记忆监测研究
- Author:
Jing REN
;
Xingui CHEN
;
Yongsheng HAN
;
Huijuan MA
;
Kai WANG
- Publication Type:Journal Article
- Keywords:
Wilson's disease;
Memory monitoring;
Feeling-of-knowing
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2014;23(5):420-422
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the memory monitoring ability in patients with hepatolenticular degeneration(HLD) and explore the mechanism of their memory impairment.Methods The feeling-of-knowing (FOK) paradigm of episodic memory(EM) and semantic memory(SM)were established and subsequently applied to 30 HLD patients and 30 healthy control(HC) participants who were matched in age and educational level.Results Compared with healthy control group (FOK-EM recall (64.17 ± 29.21) ％ ; FOK-SM recall (84.72 ± 11.44)％),the FOK-EM recall((26.55±20.92)％) and FOK-SM recall((53.93±28.42)％) in HLD patients were significantly lower(t=-5.140,P＜0.01 ; t=-5.123,P＜0.01).The positive judgment and correct recognition of FOK-EM ((50.64±29.43) ％) and the negative judgment and correct recognition of FOK-EM((12.80± 18.32) ％) in the HLD group were significantly different from the HC group (the positive judgment and correct recognition of FOK-EM:(75.15±31.73)％ and the false judgment and correct recognition of FOK-EM:(1.81±5.41)％; t=-2.693,P＜0.05 ; t=3.026,P＜0.01).Most importantly,the stroop effect was positively correlated with the negative judgment and correct recognition of FOK-EM in HLD group(r=0.601,P＜0.01).Conclusion The results show that the HLD group underestimate their memory performance on episodic FOK,and the impairment of memory monitoring is positively correlated with the deficit of executive function,indicating that the prefrontal impairment can be an influential factor of memory disorder in HLD,whereas the unimpaired semantic metamemory FOK indicates the episodic and semantic metamemory monitoring may depend on different neural network.
